Overview

abess-package

abess: Fast Best Subset Selection

Generalized linear model

abess(<default>) abess(<formula>)

Adaptive best subset selection (for generalized linear model)

coef(<abess>)

Extract Model Coefficients from a fitted "abess" object.

deviance(<abess>)

Extract the deviance from a fitted "abess" object.

extract()

Extract one model from a fitted "abess" object.

plot(<abess>)

Creat plot from a fitted "abess" object

predict(<abess>)

Make predictions from a fitted "abess" object.

print(<abess>)

Print method for a fitted "abess" object

Principal component analysis

abesspca()

Adaptive best subset selection for principal component analysis

coef(<abesspca>)

Extract Sparse Loadings from a fitted "abesspca" object.

plot(<abesspca>)

Creat plot from a fitted "abess" object

print(<abesspca>)

Print method for a fitted "abesspca" object

Robust principal component analysis

abessrpca()

Adaptive best subset selection for robust principal component analysis

coef(<abessrpca>)

Extract sparse component from a fitted "abessrpca" object.

plot(<abessrpca>)

Creat plot from a fitted "abessrpca" object

print(<abessrpca>)

Print method for a fitted "abessrpca" object

Synthetic datasets

generate.data()

Generate simulated data

generate.matrix()

Generate matrix composed of a sparse matrix and low-rank matrix

generate.spc.matrix()

Generate matrix with sparse principal component

Real-world dataset

trim32

The Bardet-Biedl syndrome Gene expression data